software.amazon.awssdk.services.glue.model

Class FindMatchesMetrics

java.lang.Object

software.amazon.awssdk.services.glue.model.FindMatchesMetrics

All Implemented Interfaces:

Serializable, SdkPojo, ToCopyableBuilder<FindMatchesMetrics.Builder,FindMatchesMetrics>

@Generated(value="software.amazon.awssdk:codegen")
public final class FindMatchesMetrics
extends Object
implements SdkPojo, Serializable, ToCopyableBuilder<FindMatchesMetrics.Builder,FindMatchesMetrics>

The evaluation metrics for the find matches algorithm. The quality of your machine learning transform is measured by getting your transform to predict some matches and comparing the results to known matches from the same dataset. The quality metrics are based on a subset of your data, so they are not precise.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	FindMatchesMetrics.Builder

Method Summary

Modifier and Type	Method and Description
Double	areaUnderPRCurve() The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs.
static FindMatchesMetrics.Builder	builder()
ConfusionMatrix	confusionMatrix() The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.
boolean	equals(Object obj)
boolean	equalsBySdkFields(Object obj)
Double	f1() The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.
<T> Optional<T>	getValueForField(String fieldName, Class<T> clazz)
int	hashCode()
Double	precision() The precision metric indicates when often your transform is correct when it predicts a match.
Double	recall() The recall metric indicates that for an actual match, how often your transform predicts the match.
List<SdkField<?>>	sdkFields()
static Class<? extends FindMatchesMetrics.Builder>	serializableBuilderClass()
FindMatchesMetrics.Builder	toBuilder()
String	toString() Returns a string representation of this object.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder

copy

Method Detail

areaUnderPRCurve

public Double areaUnderPRCurve()

The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.

For more information, see Precision and recall in Wikipedia.

Returns:

The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.

For more information, see Precision and recall in Wikipedia.

precision

public Double precision()

The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.

For more information, see Precision and recall in Wikipedia.

Returns:

The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.

For more information, see Precision and recall in Wikipedia.

recall

public Double recall()

The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.

For more information, see Precision and recall in Wikipedia.

Returns:

The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.

For more information, see Precision and recall in Wikipedia.

f1

public Double f1()

The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.

For more information, see F1 score in Wikipedia.

Returns:

The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.

For more information, see F1 score in Wikipedia.

confusionMatrix

public ConfusionMatrix confusionMatrix()

The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.

For more information, see Confusion matrix in Wikipedia.

Returns:

The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.

For more information, see Confusion matrix in Wikipedia.

toBuilder

public FindMatchesMetrics.Builder toBuilder()

Specified by:

toBuilder in interface ToCopyableBuilder<FindMatchesMetrics.Builder,FindMatchesMetrics>

builder

public static FindMatchesMetrics.Builder builder()

serializableBuilderClass

public static Class<? extends FindMatchesMetrics.Builder> serializableBuilderClass()

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

equalsBySdkFields

public boolean equalsBySdkFields(Object obj)

Specified by:

equalsBySdkFields in interface SdkPojo

toString

public String toString()

Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.

Overrides:

toString in class Object

getValueForField

public <T> Optional<T> getValueForField(String fieldName,
                                        Class<T> clazz)

sdkFields

public List<SdkField<?>> sdkFields()

Specified by:

sdkFields in interface SdkPojo